Supplementary Materials s35

1 1 Supplementary Materials

2 De novo assembly of cricket transcriptome 3 Transcriptome short reads were assembled de novo by ABySS then Trans-ABySS ( Birol et 4 al. 2009), Velvet-Oases ( Schulz et al. 2012) and Trinity ( Grabherr et al. 2011).

5 For the ABySS-Trans-ABySS and Velvet-Oases assembly strategies, we assembled datasets 6 from each individual using similar assembly parameters (kmer value = 43 to 91 with step of 7 4). The Velvet-Oases assembly employed Velvet (version 1.2.07) using a set of kmer values 8 (Zerbino & Birney 2008), followed by Oases (version 0.2.08) with the default parameters 9 ( Schulz et al. 2012). In ABySS-TransABySS assembly, individual kmer assemblies were carried 10 out by ABySS version 1.3.4 with the scaffolding option off and contig end erosion off ( Birol et 11 al. 2009). Trans-ABySS (version 1.3.2) was used after ABySS to merge the individual kmer 12 assemblies with default parameters ( Robertson et al. 2010). The slightly different kmer set 13 chosen for Velvet-Oases was due to its slow performance. However transcriptome assemblers 14 do not simply group transcripts by individual assemblies from a single kmer, and instead 15 gather all the transcripts and further assemble individual contigs into transcriptome. The 16 chosen kmers for the three assemblers covers a very close range, and it has been proven that 17 limiting the number of kmer values will not result in significant loss in assembly quality but 18 will instead permit savings in assembly time (Durai 2016).

19 After the initial assemblies, contigs of individual samples were merged with both strands 20 information using the accurate mode of CD-HIT-EST version 4.5.4 with the sequence identity 21 threshold at 100% and a word size of 8 (Li & Godzik 2006). Since the combined set will 22 contain small variations, such as allelic variations, small insertions or deletions, GICL (release 23 date 2010-07-22) was then used to further reduce the redundancy level( Pertea et al. 2003). 24 Contigs overlapped with at least 50 bp with a minimum identity of 95% were collapsed into 25 single contigs, and the maximum length of unmatched overhangs was set to 100 bp.

26 Whereas for the Trinity assembly, we used a merged dataset from eight individuals. 27 Trinity release 2012-06-08 was employed with the ALLPATHSLG error correction, and the 28 paired fragment length was set to 200 bp. In the redundancy removal step, only CD-HIT-EST 29 was used remove shorter transcript was entirely covered by longer one with 100% identity.

30 Performances comparisons among Trans-ABySS, Oases and Trinity 31 There were no standard criteria to evaluate the quality of transcriptome assemblies 32 ( Martin et al. 2010). Researchers usually assess the quality of an assembly mostly by looking 33 at the contiguity and accuracy of the assembly (Paszkiewicz & Studholme 2010). Here, we 34 measured results in terms of transcript completeness, accuracy, and sample specificity, to 35 compare the performance of three publicly available assemblers, Trans-ABySS, Oases and 36 Trinity.

37 Trans-AbySS and Oases, the two multiple kmer assembly tools using an assembly merging 38 stratage, outperformed Trinity, the single kmer assembler performing a single assembly with 39 combined reads. In particular, Oases performed the best among the three assemblers, in 40 assembly accuracy, contiguity and sample specificity. After the initial assembly, the Trinity 41 assembly has the largest N50 and the least number of transcripts being assembled. The 42 procedure of redundancy removal applied to the Trans-ABySS and Oases assemblies has 43 greatly improved the quality of the transcriptome. In the final set of transcripts, the average 44 contig length and N50 of the Oases assembly was significantly higher than those of Trans- 45 ABySS and Trinity assemblies. Shown by the pairwise comparison, the Oases assembly 46 overlapped more of their counterpart (Suppl Table 1). Oases’s highest proportion of 47 transcripts being overlapped by other two assemblers also supports it as the best assembler 48 in this study by transcript contiguity. Contiguity indices such as N50 can give an indication 49 about how fragmented the recovered transcripts are.

50 RNA-Seq analyses often deal with multiple samples. The greatest concern for assembling 51 samples individually is the increase of redundant transcripts, while assembling all samples at 52 the initial step may result in the loss of sample-specific transcripts. We compared the sample 53 specificity of different merging strategies in transcriptome assemblies in this study. For the 54 Trans-ABySS and Oases assemblies merged from individual assemblies, in the initial stage 55 they had more contigs that were much larger than those of Trinity. The merging of assemblies 56 from individual samples using CD-Hit and GICL had greatly reduced the total number and size 57 of transcripts and increase N50s (Suppl Table 2). The Trinity assembly based on merging all 58 reads across all samples did not increase the proportion of mappable reads (Suppl Table 1). 59 Although Trinity in principle provides additional information about isoform/paralog/allele 60 structure of the transcriptome ( Grabherr et al. 2011), the low mapping percentage in sample 61 specificity has shown that many of the isoforms assembled by Trinity may not truly reflect the 62 real data. 2

4 5 63 Due to lack of genomic resources for the Australian black field cricket, the completeness 64 of the transcriptomes was firstly measure by the BLAST search to an existing Hawaiian 65 trigonidiine cricket gene index. Although the total number of hits from Oases assembly is 66 slightly lower than that of from Trans-ABySS assembly, the number of high quality hits from 67 Oases is higher. However, the completeness of the Hawaiian trigonidiine cricket gene index is 68 remaining unknown, the number of hits to the Hawaiian trigonidiine cricket gene index 69 cannot be used as an indication of transcriptome completeness, the Drosopila transcriptome 70 from Flybase were considered as ‘gold standard’ reference in our studies. Among the three 71 assemblers, Oases had the highest number of hits and high quality hits to the Drosophila 72 transcriptome, it also had the highest number of high quality unique Drosophila transcript 73 hits.

74 Transcriptome Annotation 75 Gene name assignment is crucial for drawing biologically meaningful conclusions from 76 RNA-seq experiments and for comparing results among different studies. Vijay and colleagues 77 ( Vijay et al. 2013) suggested that in assigning orthologous genes from distantly related 78 genomes, BLAST-based orthorlogy detection such as BLAST2GO would potentially have 79 higher assignment success than suffix-tree based methods such as NUCmer and PROmer 80 ( Kurtz et al. 2004). Stringent filtering on blast scores, alignment length and reciprocal-best- 81 hits are thus crucial to guard against false detection of orthologous genes ( Chen et al. 2007).

82 To functionally annotate the cricket transcriptome, the final assembled transcripts (≥200 83 bp) were submitted for homology and annotation searches using Blast2GO software (version 84 2.4.4; http://www.blast2go.org/webcite). For BLASTX against the NR database, the threshold 85 was set to E-value≤10-6. GO classification was achieved using WEGO software ( Ye et al. 2006). 86 Enzyme codes were extracted and Kyoto Encyclopedia of Genes and Genomes (KEGG) 87 ( Kanehisa et al. 2004) pathways were retrieved from KEGG web server 88 (http://www.genome.jp/kegg/).

89 Using BLAST2GO (version 2.4.4), we were able to assign gene annotations to 46,774 of the 90 80,476 transcripts from the Oases assembly. Gene ontologies (GOs) were also assigned to the 91 assembled transcripts by BLAST2GO. There were a total of 90,357 gene ontology (GO) terms 92 on all GO-levels associated with the 46,774 identified genes. Of these, assignments to level two

93 GO-terms Molecular Function (40,244) made up the highest category, followed by Biological 94 Process (33,225) and Cellular Components (16,888).

96 Supplementary Results

97 Gene ontology analysis 98 We also found that females reared in the calling treatment and males in the silent 99 treatment overexpressed Osiris proteins compared to females in the silent treatment and 100 males in the calling treatment, respectively. The Osiris gene family is a family of 101 approximately 20 genes first described in D. melanogaster that are highly conserved and only 102 found within insects ( Shah et al. 2012). Although the genes are still of unknown function, they 103 are the molecular basis of the unique Triplo-lethal locus ( Lindsley et al. 1972) and have a 104 secretion signal peptide and four domains, one of those being a putative transmembrane 105 domain.

106 Functional gene expression analysis 107 Although we did not study mating, spermatogenesis, CHC pheromonal communication, or 108 learning in this study, these aspects have were the focus of previous studies in this and a 109 sister-species, T. oceanicus (Gray & Simmons 2013). As these studies followed a similar 110 protocol, we discuss the genes associated with mating and oogenesis in greater detail here.

111 Males reared in silence 112 The results regarding spermatogenesis and mating behavior in our males reared in 113 silence are unfortunately not as clear as our other gene-phenotype associations specifically 114 examined in our experiment. For example, males in reared in silence also overexpressed 115 single genes associated with mating success (yellow) ( Drapeau et al. 2006), and successful 116 spermatogenesis (Receptor for Activated C Kinase 1) ( Kadrmas et al. 2007). Nonetheless, we 117 mention then here as exploring these candidate genes in future research specifically 118 examining sperm competitive ability and mating behavior may prove fruitful.

119 Females reared in silence

120 Females in the silent treatment only increase a single gene involved in mating decisions, 121 pale, a gene associated with increased attractiveness between males and may also increase 122 receptivity of females ( Liu et al. 2009).

8 9 123 Females reared with recorded calls 124 The calling treatment increased the expression of genes associated with mating and 125 sexual communication. Females increased expression of Desaturase 1, which is associated 126 with sexual communication through pheromones ( Houot et al. 2012; Marcillac et al. 2005), 127 and along with increased oogenesis, spinster is also associated with increased mate receptivity 128 ( Nakano et al. 2001). These results may help explain why females reared in higher densities of 129 calls show increased receptivity and motivation to find males when searching ( Kasumovic et 130 al. 2012).

131 Males reared with recorded calls 132 Four wheel drive is also associated with an increase in spermatogenesis during cytokinesis 133 ( Brill et al. 2000; Giansanti et al. 2007; Polevoy et al. 2009) which may explain why T. 134 oceanicus males reared in a calling environment demonstrate greater sperm viability (Gray & 135 Simmons 2013). In line with these increases in spermatogenesis, males also overexpressed 136 spargel, a gene whose expression is associated with increased energy metabolism associated 137 with mitochondrial regulation ( Rera et al. 2011; Tiefenböck et al. 2010). However, males 138 reared in our calling treatment also demonstrated an increased expression of Nascent 139 polypeptide associated complex protein alpha subunit ( Perrimon et al. 1996) and 140 Chromodomain-helicase-DNA-binding protein 1 (Konev et al. 2007; McDaniel et al. 2008), 141 genes associated with decreased fertility, in part due to decreased success in zygotic mitoses 142 ( Konev et al. 2007); these gene expression results do not support the results from T. 143 oceanicus. In addition, although males from the silent treatment had an increased expression 144 of lingerer, a gene associated with increased copulation duration ( Kuniyoshi et al. 2002), 145 males also had increased expression of discs large 1 where mutants show decreased mating 146 behaviour.

147 Learning and memory 148 In addition to the above, we also observed several unique genes involved in learning and 149 memory expressed by males and females from the different treatments (Figure 3, 150 Supplemental Excel file). Of these treatment by sex combinations, females reared in the silent 151 treatment increased the expression of three different genes: CRMP (Morris et al. 2012), 152 Ankyrin 2 (Iqbal et al. 2013), and Argonaute-1 ( McCann et al. 2011) where disruption of the

153 latter two results in cognitive impairment in learning and memory. Males in the silent 154 treatment increased expression of cAMP-dependent protein kinase 1 associated with memory 155 increases ( Horiuchi et al. 2008) and learning ( Li et al. 1996; Skoulakis et al. 1993) and 156 Neuroglian which is positively associated with neurogenesis ( Carhan et al. 2005; Yamamoto et 157 al. 2006). In contrast, females in the calling treatment only expressed a single unique gene, 158 aru, which is associated with memory formation ( Laferriere et al. 2011), and males in the 159 calling treatment increased expression of lethal (2) giant larvae, which is involved in 26 160 different biological processes associated with neuronal and nervous system development.

161 Our results may help explain as to why individuals form other species that are reared 162 under non-social conditions (in our case, in silence) can possess improved learning and 163 memory retention (Wongwitdecha & Marsden 1996). Future studies will be necessary to 164 determine whether T. commodus reared in silence also have improved learning and memory.

165 Transcription factors

166 Here we outline the identified transcription factors that were not directly related to our 167 phenotypic study, but yield interesting information for future studies in this and other 168 organisms.

169 170 Individuals in the silent treatment

171 Two other transcription factors seem to play a greater role in males. The first, spalt- 172 related, is associated with male genital development ( Si-Dong et al. 2003) and is also associated 173 with antennal development and the sensory perception of sound ( Dong et al. 2002). Sound 174 perception in Drosophila, however, is associated with antennal development, which is not the case 175 in crickets. Thus, whether spalt-related has the same role in T. commodus is unknown. The second 176 gene, extra macrochaetae, is associate with inter-male aggression ( Edwards et al. 2009), 177 spermatid development ( Castrillon et al. 1993) and brain development ( Yamamoto et al. 2008).

178 Individuals from the calling treatment

179 Individuals from the calling treatment also showed an overexpression of transcription 180 factors associated with reproduction: daughterless coordinates differentiation during follicle 181 formation ( Smith et al. 2002), and spindle E is involved in 14 different roles associated with 182 meiosis and oogenesis ( Zhang et al. 2000). These fall in line with our results that females from 183 the calling treatment produced more eggs through their lifetime.

12 13 184 Expressed by females

185 Females expressed four unique transcription factors associated with neurogenesis when 186 compared to males. Domino is a chromatin regulator that, among being associated with E2F (a 187 key regulator of cell proliferation and differentiation, ( Parrish et al. 2006), it regulates 188 dendrite development resulting in a greater number of longer branches ( Iyer et al. 2013; Ruhf 189 et al. 2001). A second transcription factor, cubitus interruptus, is a component of hedgehog 190 signaling and is essential for the development of dorsal class I da neurons ( Parrish et al. 191 2006). Leonardo (14-3-3ζ) is a gene that regulates protein folding and stabilizations ( Yano et 192 al. 2006). In regards to our study, Leonardo is of particular interest as it is involved in 193 facilitating olfactory learning and long-term memory in Drosophila ( Philip et al. 2001). These 194 neuronal and sensory system transcription factors are likely to be particularly relevant for 195 females as they are the mate-searching species.

196 Expressed by males

197 neutralized and schnurri, are associated with neurogenesis ( Yamamoto et al. 2008) and 198 learning ( Dubnau et al. 2003), respectively. The other two transcription factors are not well 199 documented; PNUTS, is associated with development and growth, however little is known 200 about its exact function ( Ciurciu et al. 2013) and female sterile, is associated with 201 gametogenesis in females ( Wieschaus et al. 1978).

202 Learning and Memory

203 We also found an overexpression of transcription factors associated with neuronal 204 development. Interestingly there was a mixture of genes that positively and negatively 205 regulate neuronal branching. There was an increase in expression of 14-3-3ε, which, although 206 involved in axon guidance, is not documented to play as central a role in neuronal 207 development as Leonardo (Yang & Terman 2012). Two other transcription factors negatively 208 regulated neurogenesis; Sin3A functions in transcriptional repression ( Parrish et al. 2006) 209 and brain tumor negatively regulates cell proliferation in brain development ( Bello et al. 210 2006) and neuromuscular junctions ( Shi et al. 2013). We also found an overexpression of 211 three other transcription factors that are associated with neurogenesis according to FlyBase: 212 Without children, brahma, and daughterless; however, their exact role in brain development is 213 not well characterized. 7

14 15 214

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